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AUTOMATIC ADAPTIVE 3‐D FINITE ELEMENT REFINEMENT USING DIFFERENT‐ORDER TETRAHEDRAL ELEMENTS
Author(s) -
LEE C. K.,
LO S. H.
Publication year - 1997
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/(sici)1097-0207(19970630)40:12<2195::aid-nme153>3.0.co;2-3
Subject(s) - tetrahedron , degrees of freedom (physics and chemistry) , finite element method , conjugate gradient method , solver , convergence (economics) , rate of convergence , mathematics , mixed finite element method , adaptive mesh refinement , mesh generation , algorithm , mathematical optimization , computer science , geometry , computational science , structural engineering , physics , engineering , computer network , channel (broadcasting) , quantum mechanics , economics , economic growth
Automatic refinement finite element analyses were carried out employing three different‐order tetrahedral solid elements for the solution of 3‐D stress analysis problems. Numerical results indicated that the adaptive refinement procedure could eliminate effectively the effect of singularities and the optimal convergence rate was achieved in all the examples tested. The preconditioned conjugate gradient technique was used for the solution of the large system of simultaneous equations. By interpolating the initial guess of the iteration solver from the previous converged solution, the number of iterations needed for the solution is lower than expected. Furthermore, when the mesh density distribution pattern has converged, it became even more efficient and independent of the number of degrees of freedom in the finite element mesh. The relative efficiency of the three different‐order tetrahedral elements has also been compared in terms of storage and computational cost needed for achieving a certain accuracy. It is found that although the cubic T20 element can achieve the highest convergence rate, the T10 element is the most competitive and effective element in terms of storage and computational cost needed. © 1997 John Wiley & Sons, Ltd.